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By: (Edited by) Alfredo Petrosino , (Edited by) Lucia Maddalena , (Edited by) Sankar K. Pal
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This handbook illustrates the application of soft computing techniques to different tasks in video surveillance. After an introduction to video surveillance systems and soft computing tools, the book gives examples of neural network-based approaches for solving video surveillance tasks and describes summarization techniques for content identification. Covering a broad spectrum of video surveillance topics, the remaining chapters explain how soft computing techniques are used to detect moving objects, track objects, and classify and recognize target objects. The book also explores advanced surveillance systems under development.
Information on integrating soft computing techniques into video surveillance is widely scattered among conference papers, journal articles, and books. Bringing this research together in one source, Handbook on Soft Computing for Video Surveillance illustrates the application of soft computing techniques to different tasks in video surveillance. Worldwide experts in the field present novel solutions to video surveillance problems and discuss future trends.
After an introduction to video surveillance systems and soft computing tools, the book gives examples of neural network-based approaches for solving video surveillance tasks and describes summarization techniques for content identification. Covering a broad spectrum of video surveillance topics, the remaining chapters explain how soft computing techniques are used to detect moving objects, track objects, and classify and recognize target objects. The book also explores advanced surveillance systems under development.
Incorporating both existing and new ideas, this handbook unifies the basic concepts, theories, algorithms, and applications of soft computing. It demonstrates why and how soft computing methodologies can be used in various video surveillance problems.
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